The Predictive Power of Alternative Volatility Forecasting Models over Multiple Horizons

2016

Master thesis Business Administration - University of Agder 2016 This thesis paper examines the forecast accuracy and explanatory power of volatility models over multiple forecast horizon for three asset classes. Forecast horizon ranging from 1 month up to 12 subsequent months are investigated using Naïve, EWMA, GARCH, EGARCH, GJR-GARCH and APARCH model for S&P 500, DJIA, CBOE(^TNX ), CBOE(^FVX), USD/CHF and GBP/CHF. MSE and Predictive Power (𝑃�) are used to evaluate the forecast accuracy and predictive ability of the model over increasing horizon. Different distribution assumptions are also included with non-linear GARCH models in an attempt to improve forecast accuracy of the models. The…